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Won, Sungho,Choi, Hosik,Park, Suyeon,Lee, Juyoung,Park, Changyi,Kwon, Sunghoon Hindawi Publishing Corporation 2015 BioMed research international Vol.2015 No.-
<P>Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases. However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model. Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called “large P and small N” problem. Penalized regressions including least absolute selection and shrinkage operator (LASSO) and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs. Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases. Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration.</P>
Extension of the Haseman-Elston Regression Model to Longitudinal Data
Won, Sungho,Elston, Robert C.,Park, Taesung S. Karger AG 2006 Human heredity Vol.61 No.2
<P>We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene × time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well.</P><P>Copyright © 2006 S. Karger AG, Basel</P>
Won, Sungho,Lu, Qing,Bertram, Lars,Tanzi, Rudolph E.,Lange, Christoph S. Karger AG 2012 Human heredity Vol.73 No.1
<P>For the meta-analysis of genome-wide association studies, we propose a new method to adjust for the population stratification and a linear mixed approach that combines family-based and unrelated samples. The proposed approach achieves similar power levels as a standard meta-analysis which combines the different test statistics or p values across studies. However, by virtue of its design, the proposed approach is robust against population admixture and stratification, and no adjustments for population admixture and stratification, even in unrelated samples, are required. Using simulation studies, we examine the power of the proposed method and compare it to standard approaches in the meta-analysis of genome-wide association studies. The practical features of the approach are illustrated with a meta-analysis of three genome-wide association studies for Alzheimer’s disease. We identify three single nucleotide polymorphisms showing significant genome-wide association with affection status. Two single nucleotide polymorphisms are novel and will be verified in other populations in our follow-up study.</P><P>Copyright © 2012 S. Karger AG, Basel</P>
Won, Sungho,Kim, Wonji,Lee, Sungyoung,Lee, Young,Sung, Joohon,Park, Taesung BioMed Central 2015 BMC bioinformatics Vol.16 No.-
<P><B>Background</B></P><P>Many disease phenotypes are outcomes of the complicated interplay between multiple genes, and multiple phenotypes are affected by a single or multiple genotypes. Therefore, joint analysis of multiple phenotypes and multiple markers has been considered as an efficient strategy for genome-wide association analysis, and in this work we propose an omnibus family-based association test for the joint analysis of multiple genotypes and multiple phenotypes.</P><P><B>Results</B></P><P>The proposed test can be applied for both quantitative and dichotomous phenotypes, and it is robust under the presence of population substructure, as long as large-scale genomic data is available. Using simulated data, we showed that our method is statistically more efficient than the existing methods, and the practical relevance is illustrated by application of the approach to obesity-related phenotypes.</P><P><B>Conclusions</B></P><P>The proposed method may be more statistically efficient than the existing methods. The application was developed in C++ and is available at the following URL: http://healthstat.snu.ac.kr/software/mfqls/.</P>
Introduction of Mobile-based Interactive Identification Key
Suwon Chun,Sungho Choi,Won-Young Choi,Yang-Seop Bae 한국응용곤충학회 2016 한국응용곤충학회 학술대회논문집 Vol.2016 No.04
Species identification, the process of finding the taxon to which a specimen belongs, is a difficult and frustrating task for most biologists but is absolutely fundamental to most biological research. However, proper species identification requires extensive knowledge on the particular taxon, thus can be problematic and confusing for non-professionals. To increase the accuracy of identification, computer-based interactive identification key has been widely used. In order to improve the identification process and promote effective utilization of Korean species, Korean Indigenous Interactive Key System (KIIS) was developed. Moreover, image-based online identification system was developed to broaden the range of users from non-experts to professionals. As the use of mobile device became significant in people’s lives, we further developed mobile web-based identification system.
Ye An Kim,Ji Won Yoon,Young Lee,최혁진,Jae Won Yun,Eunsin Bae,Seung-Hyun Kwon,So Eun Ahn,Ah-Ra Do,Heejin Jin,Sungho Won,Do Joon Park,Chan Soo Shin,서제현 대한내분비학회 2021 Endocrinology and metabolism Vol.36 No.6
Background: Epidemiological data have shown that vitamin D deficiency is highly prevalent in Korea. Genetic factors influencing vitamin D deficiency in humans have been studied in Europe but are less known in East Asian countries, including Korea. We aimed to investigate the genetic factors related to vitamin D levels in Korean people using a genome-wide association study (GWAS). Methods: We included 12,642 subjects from three different genetic cohorts consisting of Korean participants. The GWAS was performed on 7,590 individuals using linear or logistic regression meta- and mega-analyses. After identifying significant single nucleotide polymorphisms (SNPs), we calculated heritability and performed replication and rare variant analyses. In addition, expression quantitative trait locus (eQTL) analysis for significant SNPs was performed. Results: rs12803256, in the actin epsilon 1, pseudogene (ACTE1P) gene, was identified as a novel polymorphism associated with vitamin D deficiency. SNPs, such as rs11723621 and rs7041, in the group-specific component gene (GC) and rs11023332 in the phosphodiesterase 3B (PDE3B) gene were significantly associated with vitamin D deficiency in both meta- and mega-analyses. The SNP heritability of the vitamin D concentration was estimated to be 7.23%. eQTL analysis for rs12803256 for the genes related to vitamin D metabolism, including glutamine-dependent NAD(+) synthetase (NADSYN1) and 7-dehydrocholesterol reductase (DHCR7), showed significantly different expression according to alleles. Conclusion: The genetic factors underlying vitamin D deficiency in Korea included polymorphisms in the GC, PDE3B, NADSYN1, and ACTE1P genes. The biological mechanism of a non-coding SNP (rs12803256) for DHCR7/NADSYN1 on vitamin D concentrations is unclear, warranting further investigations.